The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the inventors hereof, to the extent the work is described in this background section, as well as aspects of the description that do not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted to be prior art against the present disclosure.
Existing wireless communication systems often operate based on coded bits being mapped to constellation symbols, which, in turn, get mapped to multi-stream symbols. In the receive chain of receiver devices in such communication systems, after a received multi-stream symbol has been downconverted to a baseband frequency range and digitized, zero forcing equalizer circuitry typically performs zero forcing equalization on the baseband multi-stream symbol. The output of the zero forcing equalizer is passed to a log-likelihood ratio (LLR) computation block, which computes LLRs for each bit present in the zero force equalized symbol. Each LLR indicates an a measure of confidence that a particular bit was transmitted as a binary one or a binary zero. The LLRs are passed to a decoding block, which decodes the bits of the symbol. Conventional zero forcing equalizers, however, are inefficient in that they require many repetitive sequential computations to invert matrices for zero forcing equalization. Such required sequential computations increase the latency in performing zero forcing equalization upon received symbols and significant chip real estate is required to perform such computations. Additionally, conventional zero forcing equalizers de-whiten elements of a complex-valued noise vector present in received symbols. De-whitening causes the noise elements to have different noise variance values from one another and to become correlated with one another. Such de-whitening of noise vectors degrades the performance of downstream LLR computation by increasing the instances of inaccurate bit value predictions. Such inaccurate bit value predictions increase the bit error rate (BER) and/or packet error rate (PER), and thus decrease the throughput, of conventional wireless receiver systems.